Biology subjects

Qian, E.

Publications and source records attributed to Qian, E..

4 recordsLinked to original sources

bioRxiv2023

Magnetic Resonance Fingerprinting based Thermometry (MRFT): application to ex vivo imaging near DBS leads

The purpose of this study is to demonstrate the first work of T1-based magnetic resonance thermometry using magnetic resonance fingerprinting (dubbed MRFT). We compared temperature estimation of MRFT with proton resonance frequency shift (PRFS) thermometry on ex vivo bovine muscle. We demonstrated MRFTs feasibility in predicting temperature on ex vivo bovine muscles with deep brain stimulation (DBS) lead. B0 maps generated from MRFT were compared with gold standard B0 maps near the DBS lead. All experiments were performed on a 3 Tesla whole-body GE Premier system equipped with a 21-channel receive head coil (GE Healthcare, Milwaukee, WI). Four fluoroptic probes were used to measure the temperature at the center of a cold muscle (probe 1), the room temperature water bottle (probe 2), and the center and periphery of the heated muscle (probes 3 and 4). We selected regions of interest (ROIs) around the location of the probes and used simple linear regression to generate the temperature sensitivity calibration equations that convert T1 maps and {Delta}s maps to temperature maps. We then repeated the same setup and compared MRFT, PRFS thermometry temperature estimation with gold standard probe measurements. For the MRFT experiment on DBS lead, we taped the probe to the tip of the DBS lead and used a turbo spin echo (TSE) sequence to induce heating near the lead. We selected ROIs around the tip of the lead to compare MRFT temperature estimation with probe measurements. Vendor-supplied B0 mapping sequence was acquired to compare with MRFT-generated B0 maps. We found strong linear relationships (R2>0.958) between T1 and temperature and {Delta}s and temperatures in our temperature sensitivity calibration experiment. MRFT and PRFS thermometry both accurately predict temperature (RMSE<1.55 {degrees}C) compared to probe measurements. MRFT estimated temperature near DBS lead has a similar trend as the probe temperature. Both B0 maps show inhomogeneities around the lead.

bioengineering↗

bioRxiv2021

Minor intron splicing efficiency increases with the development of lethal prostate cancer

Here we explored the role of minor spliceosome (MiS) function and minor intron-containing gene (MIG) expression in prostate cancer (PCa). We show MIGs are enriched as direct interactors of cancer-causing genes and their expression discriminates PCa progression. Increased expression of MiS U6atac snRNA, including others, and 6x more efficient minor intron splicing was observed in castration-resistant PCa (CRPC) versus primary PCa. Notably, androgen receptor signalling influenced MiS activity. Inhibition of MiS through siU6atac in PCa caused minor intron mis-splicing and aberrant expression of MIG transcripts and encoded proteins, which enriched for MAPK activity, DNA repair and cell cycle. Single cell-RNAseq confirmed cell cycle defects and lineage dependency on the MiS from primary to CRPC and neuroendocrine PCa. siU6atac was [~]50% more efficient in lowering tumor burden of CRPC cells and organoids versus current state-of-the-art combination therapy. In all, MiS is a strong therapeutic target for lethal PCa and potentially other cancers. Graphical AbstractU6atac expression, MiS activity, and minor intron splicing correlate with PCa therapy resistance and PCa progression to CRPC-adeno and transdifferentiation to CRPC-NE. One major MiS regulator during that process is the AR-axis, which is re-activated during CRPC-adeno and blocked in CRPC-NE. Molecularly, an increase in MiS dependent splicing promotes changes of transcriptome and proteome. This results in cell cycle activation, increased MAPK signalling and increased DNA repair. U6atac mediated MiS inhibition renders MiS splicing error-prone through increased intron retention and alternative splicing events, which results in cell cycle block and decreased MAPK signalling and DNA repair. MiS inhibition blocks all stages of PCa. Figure created with BioRender.com. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/471104v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@1c1c296org.highwire.dtl.DTLVardef@1ce1416org.highwire.dtl.DTLVardef@88d842org.highwire.dtl.DTLVardef@2ddf96_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Debates about vaccines and climate change on social media networks: a study in contrasts

Vaccines and climate change have much in common. In both cases, a scientific consensus contrasts with a divided public opinion. They also exemplify coupled human-environment systems involving common pool resources. Here we used machine learning algorithms to analyze the sentiment of 87 million tweets on climate change and vaccines in order to characterize Twitter user sentiment and the structure of user and community networks. We found that the vaccine conversation was characterized by much less interaction between individuals with differing sentiment toward vaccines. Community-level interactions followed this pattern, showing less interaction between communities of opposite sentiment toward vaccines. Additionally, vaccine community networks were more fragmented and exhibited numerous isolated communities of neutral sentiment. Finally, pro-vaccine individuals overwhelmingly believed in anthropogenic climate change, but the converse was not true. We propose mechanisms that might explain these results, pertaining to how the spatial scale of an environment system can structure human populations.

ecology↗

bioRxiv2019

Considerations for clinical curation, classification and reporting of low-penetrance and low effect size variants associated with disease risk

PurposeClinically relevant variants exhibit a wide range of penetrance. Medical practice has traditionally focused on highly penetrant variants with large effect sizes and, consequently, classification and clinical reporting frameworks are tailored to that variant type. At the other end of the penetrance spectrum, where variants are often referred to as "risk alleles", traditional frameworks are no longer appropriate. This has led to inconsistency in how such variants are interpreted and classified. Here, we describe a conceptual framework to begin addressing this gap. MethodsWe used a set of risk alleles to define data elements that can characterize the validity of reported disease associations. We assigned weight to these data elements and established classification categories expressing confidence levels. This framework was then expanded to develop criteria for inclusion of risk alleles on clinical reports. ResultsFoundational data elements include cohort size, quality of phenotyping, statistical significance, and replication of results. Criteria for determining inclusion of risk alleles on clinical reports include presence of clinical management guidelines, effect size, severity of the associated phenotype, and effectiveness of intervention. ConclusionsThis framework represents an approach for classifying risk alleles and can serve as a foundation to catalyze community efforts for refinement.

genetics↗